• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.11
• /
• pp.3970-3990
• /
• 2021

In view of the problems of insufficient data collection and processing capability of multi-source heterogeneous equipment, and low visibility of equipment status at the ship block construction site. A data collection method for ship block construction equipment based on wireless sensor network (WSN) technology and a data processing method based on edge computing were proposed. Based on the Browser/Server (B/S) architecture and the OneNET platform, an online monitoring system for ship block construction equipment was designed and developed, which realized the visual online monitoring and management of the ship block construction equipment status. Not only that, the feasibility and reliability of the monitoring system were verified by using the intelligent tire frame system as the application object. The research of this project can lay the foundation for the ship block construction equipment management and the ship block intelligent construction, and ultimately improve the quality and efficiency of ship block construction.

• The Journal of Korea Robotics Society
• /
• v.18 no.3
• /
• pp.346-351
• /
• 2023

With the release of numerous open driving datasets, the demand for domain adaptation in perception tasks has increased, particularly when transferring knowledge from rich datasets to novel domains. However, it is difficult to solve the change 1) in the sensor domain caused by heterogeneous LiDAR sensors and 2) in the environmental domain caused by different environmental factors. We overcome domain differences in the semi-supervised setting with 3-stage model parameter training. First, we pre-train the model with the source dataset with object scaling based on statistics of the object size. Then we fine-tine the partially frozen model weights with copy-and-paste augmentation. The 3D points in the box labels are copied from one scene and pasted to the other scenes. Finally, we use the knowledge distillation method to update the student network with a moving average from the teacher network along with a self-training method with pseudo labels. Test-Time Augmentation with varying z values is employed to predict the final results. Our method achieved 3rd place in ECCV 2022 workshop on the 3D Perception for Autonomous Driving challenge.

• Journal of Positioning, Navigation, and Timing
• /
• v.13 no.3
• /
• pp.289-299
• /
• 2024

In the Pedestrian Dead Reckoning (PDR)/Global Positioning System (GPS)/Wi-Fi-integrated navigation system for indoor/outdoor continuous positioning of pedestrians, the process of detecting outliers in measurements is very important. When accurate location information from measurements is used, reliable correction data can be generated during the fusion filtering process. However, abnormal measurements may occur in certain situations, such as indoor/outdoor transitions, which can degrade filter performance and lead to significant errors in the estimated position. To address this issue, this paper proposes a method for detecting outliers in measurements based on Rényi Divergence (RD). When the deviation of the RD value is large, the measurements are considered outliers, and positioning is performed using only pure PDR. Based on experiments conducted with real data, it was confirmed that outliers were effectively detected for abnormal measurements, leading to an improvement in the performance of pedestrian navigation.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.5C
• /
• pp.355-364
• /
• 2012

Target processing mechanisms are necessary to collect target information, real-time data fusion, and tactical environment recognition for cooperative engagement ability. Among these mechanisms, the target tracking starts from predicting state of speed, acceleration, and location by using sensors' measurements. However, it can be a problem to give the reliability because the measurements have a certain uncertainty. Thus, a technique which uses multiple sensors is needed to detect the target and increase the reliability. Also, data fusion technique is necessary to process the data which is provided from heterogeneous sensors for target tracking. In this paper, a target tracking algorithm is proposed based on probabilistic data association(PDA) by fusing radar and ESM sensor measurements. The radar sensor's azimuth and range measurements and the ESM sensor's bearing-only measurement are associated by the measurement fusion method. After gating associated measurements, state estimation of the target is performed by PDA filter. The simulation results show that the proposed algorithm provides improved estimation under linear and circular target motions.

• KIISE Transactions on Computing Practices
• /
• v.21 no.1
• /
• pp.64-69
• /
• 2015

Place awareness is an essential for location-based services that are widely provided to smartphone users. However, traditional GPS-based methods are only valid outdoors where the GPS signal is strong and also require symbolic place information of the physical location. In this paper, environmental sounds and images are used to recognize important aspects of each place. The proposed method extracts feature vectors from visual, auditory and location data recorded by a smartphone with built-in camera, microphone and GPS sensors modules. The heterogeneous feature vectors were then learned by an ensemble learning method that learns each group of feature vectors for each classifier respectively and votes to produce the highest weighted result. The proposed method is evaluated for place recognition using a data group of 3000 samples in six places and the experimental results show a remarkably improved recognition accuracy when using all kinds of sensory data comparing to results using data from a single sensor or audio-visual integrated data only.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.18 no.1
• /
• pp.47-58
• /
• 2018

The heterogeneous cellular network (HCN) is most significant as a key technology for future fifth generation (5G) wireless networks. The heterogeneous network considered consists of randomly macrocell base stations (MBSs) overlaid with femtocell base stations (BSs). The stochastic geometry has been shown to be a very powerful tool to model, analyze, and design networks with random topologies such as wireless ad hoc, sensor networks, and multi- tier cellular networks. The HCNs can be energy-efficiently designed by deploying various BSs belonging to different networks, which has drawn significant attention to one of the technologies for future 5G wireless networks. In this paper, we propose switching off/on systems enabling the BSs in the cellular networks to efficiently consume the power by introducing active/sleep modes, which is able to reduce the interference and power consumption in the MBSs and FBSs on an individual basis as well as improve the energy efficiency of the cellular networks. We formulate the minimization of the power onsumption for the MBSs and FBSs as well as an optimization problem to maximize the energy efficiency subject to throughput outage constraints, which can be solved the Karush Kuhn Tucker (KKT) conditions according to the femto tier BS density. We also formulate and compare the coverage probability and the energy efficiency in HCNs scenarios with and without coordinated multi-point (CoMP) to avoid coverage holes.

• Journal of the Korean Electrochemical Society
• /
• v.11 no.2
• /
• pp.105-108
• /
• 2008

In the recent years, increasing interests are being focused on the rational functionalization of the CNTs by some creative methods. However, the considerable toxicity of CNT is still a controversialissue and limits its biological application. To improve the biocompatibility of CNT, in this work we prepared CNT-$TiO_2$ nanocomposites with CNT and organic titanium precursors. Our observations demonstratethat the modified interface could accelerate the heterogeneous electron transfer rates and thusenhance the relevant detection sensitivity, suggesting its potential application as the new strategy for the development of the biocompatible and multi-signal responsive biosensors for the early diagnosis of cancers.

• Journal of Digital Convergence
• /
• v.14 no.10
• /
• pp.295-302
• /
• 2016

Many countries, especially ICT powers, are supporting IoT-based technology at a national level and this technology is actively being researched in the businesses and research institutes in an aim to develop technology and create an ecosystem. Roads in the Seoul city are building public facilities based on IoT to provide various services and conveniences for the users. However, for the full-fledged introduction and development of IoT, there are many cases where infringement on security and privacy and threat for life and safety happen. Also, as the IoT environment includes various environment technologies such as the existing sensor network, heterogeneous communication network, and devices optimized for the IoT environment, it inherits the existing security threat and various attack techniques. This paper researches the attribute based encryption technology for safe communication in the IoT environment. The data collected from the device is transmitted utilizing the attribute based encryption and by designing the key generation protocol, grades and authorities for the device and users are identified to transmit safe messages.

• Journal of Drive and Control
• /
• v.17 no.1
• /
• pp.37-43
• /
• 2020

An intelligent excavator can be divided into Machine Guidance (MG), semi-automatic, and unmanned by technology. The MG technology excavator is equipped with a tilt sensor on each link of the excavator and a GPS is installed on the excavator body to inform the user of the position of the excavator bucket end. Machine control (MC) technology that assists the user's work can be divided into semi-automatic and fully automatic technology. The semi-automatic MC equipment has already been commercialized by Komatsu and Caterpillar. The MC excavator is equipped with an electro-hydraulic system, sensors and controllers to control the excavator bucket end according to the user's needs. In this study, the semi-automated excavator modified based on manual excavator, is equipped with an electro-hydraulic system, a controller system, multi-sensors and a control algorithm is developed to assist in excavation work such as leveling and grading. By applying the developed technology, it was possible to confirm productivity improvement compared to manual digging and leveling work. In the future, further research to improve the accuracy of the hydraulic precision control and collaborative work with heterogeneous construction equipment such as dump truck and automated collaboration tasks technology could be developed.

• Journal of Sensor Science and Technology
• /
• v.27 no.5
• /
• pp.345-351
• /
• 2018

We employed an unprecedented technique to synthesize porous $WO_3@SnO_2$ nanofibers exhibiting core-shell and fiber-in-tube configurations. Firstly, 2-methylimidazole was uniformly incorporated in as-spun nanofibers containing ammonium metatungstate hydrate and the sacrificial polymer (polyacrylonitrile). Secondly, the 2-methylimidazole on the surfaces of nanofibers was complexed with tin(II) chloride ($SnCl_2$) via simple impregnation of the as-spun nanofibers in ethanol containing tin(II) chloride dihydrate ($SnCl_2{\cdot}2H_2O$). The presence of vacant p-orbitals in tin (Sn) and the nucleophilic nitrogen on the imidazole ring allowed for the reaction between $SnCl_2$ and 2-methylimidazole, forming adducts on the surfaces of the as-spun nanofibers. The calcination of these nanofibers resulted in porous $WO_3@SnO_2$ nanofibers with a higher surface area ($55.3m^2{\cdot}g^{-1}$) and a better response to 1-5 ppm of acetone than pristine $SnO_2$ NFs synthesized using a similar method. An improved response to acetone was achieved upon functionalization of the $WO_3@SnO_2$ nanofibers with catalytic palladium nanoparticles. This work demonstrates the potential application of $WO_3@SnO_2$ nanofibers as sensing layers for chemiresistive sensory devices for the detection of acetone in exhaled breath.